Hello Everyone
I am working on a conditional optimization problem that has several correlated constraints that makes it non-convex optimization problem.
So, is there any recommendations to convert it to a convex problem?
Also, are there any optimization tools or algorithms that can be used in such case?
Best Regards
If you can state the constraints explicitly then you can probably devise a global optimization procedure to solve it. There are several to pick; search with Google these terms: "global optimization software", with "tools" and "methods" as added synonyms to the search string, and see what you find.
Another thing to do is you could remove correlated constraints so it is convex to start with, solve the problem and see if any of the constraints you removed are violated. Then selectively add those and you can of course transform them otherwise use global optimization tools liike Michael Patriksson mentioned or metaheuristic methods like Genetic Algorithms
Thanks so much Temitayo Bankole
I will try that.
Best Regards.
Mustafa Sadiq Aljumaily
A thesis and Booklet for your reference is attached. It may help you. Please go through it.
http://sunju.org/docs/thesis.pdf
http://www.ifp.illinois.edu/~angelia/L5_exist_optimality.pdf
Thanks so much Vivek Kumar Chouhan for the great references.
Best Regards
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